Enroll Course: https://www.coursera.org/learn/renqun-wangluo
In today’s interconnected world, understanding the dynamics of social networks and the principles of computational thinking is more important than ever. The course 人群与网络, offered by Peking University on Coursera, provides a comprehensive exploration of these themes, making it an excellent choice for students in fields such as information technology, sociology, and economics.
### Course Overview
This interdisciplinary elective course is designed primarily for undergraduate students, focusing on how computational thinking can be applied to classic problems in sociology and economics. The course aims to deepen students’ understanding of various social phenomena and the interactions between computing and social sciences.
### Syllabus Breakdown
The course is structured into several key modules:
1. **Network and Graph Theory**: Introduces fundamental concepts of graph theory, exploring social network structures and the processes influencing edge formation.
2. **Social Choice and Influence**: Discusses how external factors affect social network structures, emphasizing the concept of homophily.
3. **Small World Phenomenon**: Examines the existence of short paths in social networks and introduces models to understand these dynamics.
4. **Web Structure and Link Analysis**: Analyzes the structure of the World Wide Web using graph theory concepts, including link relationships and search engine ranking algorithms.
5. **Game Theory**: Introduces basic elements of game theory, exploring concepts like Nash equilibrium and social optimality.
6. **Traffic Flow Games and Auctions**: Applies game theory to model traffic networks and auction scenarios, discussing optimal strategies for participants.
7. **Search Engine Advertising Pricing**: Explores pricing mechanisms for keyword-based advertising, integrating concepts from previous modules.
8. **Relationship and Power Balance in Networks**: Discusses structural and power balance in networks, applying mathematical models to analyze these dynamics.
9. **Cascading Behavior in Networks**: Models the spread of new ideas or technologies within networks, considering factors like threshold values.
10. **Herd Behavior and Popularity**: Investigates how individual decisions are influenced by others, analyzing the distribution of popularity.
11. **Impact of Information Asymmetry on Markets**: Discusses the role of market institutions in aggregating information and the effects of information asymmetry.
12. **Voting Systems**: Analyzes various voting systems and their properties, proposing criteria for effective decision-making.
### Why You Should Enroll
This course is not just about theoretical concepts; it provides practical insights into how computational thinking can enhance our understanding of social phenomena. The blend of sociology, economics, and computer science makes it a unique offering that prepares students for real-world challenges. Whether you’re looking to enhance your analytical skills or gain a deeper understanding of social networks, this course is a valuable investment in your education.
### Conclusion
In conclusion, the 人群与网络 course on Coursera is a must-take for anyone interested in the intersection of technology and social sciences. With its comprehensive syllabus and practical applications, it equips students with the tools needed to analyze and reason about complex social issues. I highly recommend this course to anyone eager to explore the fascinating world of networks and their impact on society.
Enroll Course: https://www.coursera.org/learn/renqun-wangluo